Victorian Innovator, Charles Babbage, had big ideas. He intended to build the first ever general purpose computer, despite living in the age of steam and cogs. But he needed money to do it, and he didn’t have any. He was also notorious for alienating those who invested money in his schemes. He needed a new source of income. Perhaps he could do it through games?
He came up with the idea of building a less ‘serious’ money making machine that would capture the imagination and part people with their money as a curiositiy. His big idea was to design a machine that could play Noughts and Crosses (called at the time Tit-Tat-To) and so also create the first AI game playing machine.
He had previously used game playing (and specifically Chess) as a theoretical demonstration of his argument that machines, such as his proposed Analytical Engine, would be able to do things that were thought at the time to need human reasoning. He even did a mini-survey asking “the opinions of persons in every class of life and of all ages” to find out if people believed that playing games of skill needed human reasoning (the answer was overwhelmingly, yes!) He therefore set about analysing games, and specifically Noughts and Crosses as the simplest such game of skill that he knew.
Having seen that the number of states of the game (possible positions) of Noughts and Crosses was well within the scope of what his proposed machines could handle, he started to think more seriously about actually building one. His reasoning was that by exhibiting it and charging people to play against it, he would raise enough money to fund the completion of the Analytical Engine. After all, he thought, if it could even beat the parents at a child’s game, then any parent would want to take their child to see it.
He even thought about fun, decorative automata details such as:
“I imagined that the machine might consist of the figures of two children playing against each other, accompanied by a lamb and a cock. That the child who won the game might clap his hands whilst the cock was crowing, after which, that the child who was beaten might cry and wring his hands whilst the lamb began bleating.”
He worked out the design of the machine in general terms, determining different mechanisms that could be used and noting that they it would be far simpler than the Analytical Engine itself. A specific issue he worked on was how the machine should make a choice when two equally good options were possible as he didn’t want the machine to be predictable. He came up with the solution that it could keep a record of how many times it had won so far and use that number to make the choice between moves, so use a simple version of pseudo-randomness. An even number of wins so far meant do option 1 and an add number eant do option 2. If there were three options it would take the remainder when dividing by three. He thought that this would be opaque enough that noone watching it play would work out how it was deciding where to go. He noted that this engineering design nicely illustrated definitions of chance given by philosophers
“Chance is but the expression of man’s ignorance.” – Laplace
and poets
“All chance, design ill understood.” – Pope
Sadly, before building it, when doing his equivalent of working on the business case, he discovered others had tried making money from machines. Both a machine that made Latin verse, and another that talked had failed to make money. Combined with the time it would take him to build it, he therefore gave up on the whole money-making idea.
Perhaps if he had just had more faith in people’s interest in games (over Latin!) it would have been a success and he might have raised the money to successfully build the first computer 100 years before it eventually happened. Now, of course, the computer games industry is worth billions! (The Latin verse industry is not so strong, though of course Generative AIs are now writing poems, in living languages like English, to people’s delight, if not yet making money from doing so!)
Now, what might I build to fund my research? Donations welcome!
Paul Curzon, Queen Mary University of London
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